Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "157" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 52 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 50 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
| JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2459867 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.380024 | -0.607191 | -0.012755 | 0.209214 | -0.983051 | -0.122814 | -0.017262 | 0.091305 | 0.6902 | 0.6740 | 0.4025 | nan | nan |
| 2459866 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.265830 | -0.510659 | 0.119312 | 0.340081 | -0.845126 | -0.217346 | 0.016273 | -0.264486 | 0.6898 | 0.6747 | 0.3945 | nan | nan |
| 2459865 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.541477 | -0.300975 | -0.029222 | 0.534078 | -0.775443 | 0.332628 | 0.648202 | 0.431532 | 0.7093 | 0.6919 | 0.3666 | nan | nan |
| 2459864 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.135523 | -0.295141 | 0.548875 | -0.096132 | -0.469656 | 0.007862 | -0.017018 | 1.491173 | 0.6887 | 0.6699 | 0.4161 | nan | nan |
| 2459863 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.473867 | -0.346413 | -1.022949 | -0.621861 | -0.296009 | 0.593075 | -0.464140 | 0.475801 | 0.6834 | 0.6609 | 0.4039 | nan | nan |
| 2459862 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.610254 | -0.665837 | 1.218899 | 0.119092 | -0.818368 | 0.192240 | -0.314108 | -0.216754 | 0.6676 | 0.6851 | 0.4161 | nan | nan |
| 2459861 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.469097 | -0.281000 | -0.935326 | -0.362763 | 0.040553 | 0.592523 | -0.235968 | 0.264703 | 0.6960 | 0.6678 | 0.4227 | nan | nan |
| 2459860 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.374833 | -0.626473 | 1.049609 | 0.444880 | -0.898242 | -0.165724 | -0.322985 | -0.731306 | 0.7027 | 0.6700 | 0.4175 | nan | nan |
| 2459859 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.406577 | -0.333716 | -0.986084 | -0.458032 | 0.295402 | 0.605594 | -0.448064 | -0.466129 | 0.7101 | 0.6782 | 0.4117 | nan | nan |
| 2459858 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.602600 | -0.241300 | -1.033755 | -0.567130 | 0.165175 | 0.728280 | -0.278690 | -0.074282 | 0.7186 | 0.6828 | 0.4240 | 1.622290 | 1.413260 |
| 2459857 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | 1.082618 | 0.661283 | -0.487016 | -0.839538 | -0.101133 | -0.264116 | 0.101862 | -0.659747 | 0.0286 | 0.0266 | 0.0014 | nan | nan |
| 2459856 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 3.43% | 0.57% | 0.610785 | -0.404078 | 1.131036 | 0.595042 | -0.984068 | -0.557692 | -0.185367 | -0.871352 | 0.7096 | 0.6990 | 0.4076 | 1.678116 | 1.485516 |
| 2459855 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 4.58% | 0.00% | 0.476825 | -0.127194 | 1.064486 | 0.464197 | -0.823757 | -0.317686 | -0.260839 | -0.801407 | 0.6883 | 0.7138 | 0.4389 | 1.590740 | 1.354494 |
| 2459854 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 8.93% | 0.00% | -0.182809 | -1.181835 | -0.016652 | 2.015259 | -0.872869 | -0.472194 | -0.576413 | -0.247147 | 0.7047 | 0.7268 | 0.4385 | 1.553382 | 1.379946 |
| 2459853 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.56% | 0.123590 | -1.026975 | 0.396843 | 2.714990 | -0.532213 | -0.519885 | -0.442063 | -0.593007 | 0.7313 | 0.6760 | 0.4287 | 1.676761 | 1.469140 |
| 2459852 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 8.65% | 8.11% | -1.210296 | -0.572504 | 0.789902 | 2.404007 | -1.073907 | -0.102954 | 0.351769 | 2.573240 | 0.8104 | 0.8161 | 0.2611 | 3.887593 | 3.606006 |
| 2459851 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 11.76% | 73.26% | -0.198991 | 0.131400 | 0.876118 | 2.991345 | 0.472531 | 1.398645 | 0.699440 | 1.676492 | 0.7423 | 0.7217 | 0.3527 | 3.839891 | 2.773293 |
| 2459850 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 18.02% | 0.00% | -0.377626 | -0.757495 | 0.518910 | 2.616243 | -0.754447 | -0.117472 | 0.015504 | 0.003202 | 0.7289 | 0.7409 | 0.3580 | 1.593982 | 1.398453 |
| 2459849 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 16.67% | 0.00% | -1.450637 | -0.952059 | 0.968969 | 2.283028 | 0.147307 | -0.592901 | 2.052706 | 2.208600 | 0.7225 | 0.7355 | 0.3686 | 1.437578 | 1.256117 |
| 2459848 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 30.15% | 0.00% | -1.090368 | -0.849883 | -1.114524 | 1.625207 | 0.147334 | 0.212762 | 0.110630 | 0.669929 | 0.7013 | 0.7403 | 0.3892 | 1.380024 | 1.292558 |
| 2459847 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 3.21% | 0.00% | -1.232502 | -0.021655 | -1.068623 | 1.513002 | -0.318743 | -0.239071 | 0.361219 | 1.457929 | 0.7125 | 0.6722 | 0.4381 | 1.605278 | 1.379362 |
| 2459845 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -1.047398 | -0.604928 | -0.416150 | 3.401573 | 0.185927 | -0.489691 | 0.112285 | 0.679983 | 0.7043 | 0.7259 | 0.3980 | 2.594000 | 2.544351 |
| 2459844 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | -0.814963 | 0.258099 | -0.356884 | 2.634329 | -0.366966 | 1.024190 | -0.553822 | -2.057472 | 0.0279 | 0.0260 | 0.0013 | nan | nan |
| 2459843 | digital_ok | 0.00% | 1.20% | 0.66% | 0.00% | 15.76% | 0.00% | -1.253431 | -0.942751 | -0.643670 | 0.274191 | -0.434787 | -0.646015 | -0.059013 | -0.234030 | 0.7229 | 0.7312 | 0.4013 | 1.525892 | 1.331941 |
| 2459842 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | -0.706165 | -0.749543 | 0.365136 | -0.229992 | 0.245409 | 1.095389 | -0.065466 | 0.144335 | 0.7369 | 0.6498 | 0.2846 | 1.282990 | 1.254508 |
| 2459841 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | -0.932453 | 0.770863 | -1.063780 | 0.982640 | 0.657245 | -0.665694 | -0.436377 | -1.607467 | 0.0276 | 0.0258 | 0.0016 | nan | nan |
| 2459840 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 122.669262 | 227.079434 | 61.524115 | 76.991125 | 861.531663 | 843.284316 | 1432.279147 | 1740.517765 | 0.0200 | 0.0167 | 0.0018 | nan | nan |
| 2459839 | digital_ok | 100.00% | - | - | - | - | - | 29.078072 | 87.175376 | 126.723520 | 197.983743 | 216.280259 | 349.336095 | 1740.699192 | 2622.401217 | nan | nan | nan | nan | nan |
| 2459838 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 99.39% | 0.61% | -1.083978 | -0.357764 | -0.547630 | 1.933726 | 0.317662 | -0.043276 | -0.052236 | 0.363933 | 0.6733 | 0.6395 | 0.3929 | 0.000000 | 0.000000 |
| 2459836 | digital_ok | - | 100.00% | 100.00% | 0.00% | - | - | nan | nan | nan | nan | nan | nan | nan | nan | 0.0380 | 0.0344 | 0.0030 | nan | nan |
| 2459835 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | -1.299248 | -0.104440 | -0.578163 | 0.296121 | -0.754036 | 1.463021 | 0.073925 | -1.176793 | 0.0391 | 0.0346 | 0.0028 | nan | nan |
| 2459833 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | 0.144137 | -0.001426 | -0.167548 | -0.860262 | 0.190911 | 1.976848 | 0.094599 | -1.420719 | 0.0354 | 0.0322 | 0.0033 | nan | nan |
| 2459832 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | -0.830340 | -0.439740 | -0.765571 | 1.817392 | 1.618646 | 0.274732 | 0.844800 | 0.764062 | 0.7458 | 0.4722 | 0.5429 | 1.843093 | 1.442030 |
| 2459831 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | 1.371314 | 1.323051 | 0.650999 | 2.400587 | 0.798645 | 0.106176 | -0.673897 | -1.873058 | 0.0386 | 0.0320 | 0.0038 | nan | nan |
| 2459830 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 2.63% | -0.860568 | 0.580531 | -0.465396 | 2.794633 | -0.364886 | 0.633537 | 0.564906 | 0.093156 | 0.7487 | 0.4920 | 0.5236 | 1.691652 | 1.294634 |
| 2459829 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.65% | 99.35% | -0.787942 | 0.102340 | 0.404665 | 2.561647 | 0.080083 | -0.829704 | 1.176486 | 0.692486 | 0.6905 | 0.6068 | 0.3942 | -0.000000 | -0.000000 |
| 2459828 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 0.177973 | -0.730379 | 0.196745 | 2.129037 | 1.372649 | 0.190424 | 0.707049 | -1.394608 | 0.7430 | 0.4955 | 0.5074 | 0.000000 | 0.000000 |
| 2459827 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.477891 | -1.091793 | 0.164828 | 3.855760 | -0.515744 | -0.910168 | -0.014909 | -0.455488 | 0.0675 | 0.0627 | 0.0064 | 30.244071 | 53.323990 |
| 2459826 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 0.007480 | -0.584359 | -0.247831 | 3.546215 | 0.682953 | 0.704772 | 0.442329 | -0.679970 | 0.0651 | 0.0593 | 0.0053 | 0.000000 | 0.000000 |
| 2459825 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.353620 | -1.236827 | -0.399449 | 2.117800 | 0.178263 | -0.092951 | -0.367711 | -0.596954 | 0.0646 | 0.0559 | 0.0057 | 26.751854 | 38.578375 |
| 2459824 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.652374 | -0.601464 | -0.060862 | 2.492016 | -1.080289 | -0.529912 | 0.431487 | -0.592200 | 0.0657 | 0.0623 | 0.0071 | 19.874954 | 38.869146 |
| 2459823 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 0.665687 | -0.222077 | -0.489104 | 3.349845 | 0.133980 | 0.648113 | 0.724049 | -1.694407 | 0.0666 | 0.0559 | 0.0063 | 511.742416 | 95.254002 |
| 2459822 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 0.568871 | 0.033941 | 0.028105 | 3.229347 | 0.473909 | 0.002923 | 0.825862 | 0.717066 | 0.0660 | 0.0616 | 0.0055 | 0.905956 | 0.914355 |
| 2459821 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.846396 | -1.090945 | -0.051812 | 3.487126 | 0.886429 | 0.224948 | 0.004376 | -0.130612 | 0.0546 | 0.0503 | 0.0036 | 1.254180 | 1.251768 |
| 2459820 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.587445 | -0.802101 | 0.142724 | 3.469513 | 2.429589 | -0.366433 | 0.672678 | 0.380612 | 0.0660 | 0.0575 | 0.0058 | 1.276864 | 1.276674 |
| 2459817 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 0.219821 | -0.207873 | -0.084478 | 2.764264 | 0.173251 | 0.970001 | -0.556844 | -0.723429 | 0.0661 | 0.0692 | 0.0053 | 1.236433 | 1.232171 |
| 2459816 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | -0.080685 | 0.774731 | -0.106537 | 2.966784 | 0.670219 | 1.627446 | 0.655265 | -0.688206 | 0.8446 | 0.5818 | 0.6023 | 1.704519 | 1.436287 |
| 2459815 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.241415 | 0.712567 | -0.337809 | 2.710010 | 0.120091 | 1.502206 | 0.365129 | -1.018535 | 0.7991 | 0.6598 | 0.5299 | 1.620873 | 1.342006 |
| 2459814 | digital_ok | 0.00% | - | - | - | - | - | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459813 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | 0.000000 | 0.000000 |
auto_metrics notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | ee Shape | 0.380024 | 0.380024 | -0.607191 | -0.012755 | 0.209214 | -0.983051 | -0.122814 | -0.017262 | 0.091305 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 0.340081 | -0.510659 | 0.265830 | 0.340081 | 0.119312 | -0.217346 | -0.845126 | -0.264486 | 0.016273 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | ee Temporal Discontinuties | 0.648202 | 0.541477 | -0.300975 | -0.029222 | 0.534078 | -0.775443 | 0.332628 | 0.648202 | 0.431532 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Temporal Discontinuties | 1.491173 | -0.295141 | 0.135523 | -0.096132 | 0.548875 | 0.007862 | -0.469656 | 1.491173 | -0.017018 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Temporal Variability | 0.593075 | 0.473867 | -0.346413 | -1.022949 | -0.621861 | -0.296009 | 0.593075 | -0.464140 | 0.475801 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | ee Power | 1.218899 | 0.610254 | -0.665837 | 1.218899 | 0.119092 | -0.818368 | 0.192240 | -0.314108 | -0.216754 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Temporal Variability | 0.592523 | -0.281000 | 0.469097 | -0.362763 | -0.935326 | 0.592523 | 0.040553 | 0.264703 | -0.235968 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | ee Power | 1.049609 | 0.374833 | -0.626473 | 1.049609 | 0.444880 | -0.898242 | -0.165724 | -0.322985 | -0.731306 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Temporal Variability | 0.605594 | 0.406577 | -0.333716 | -0.986084 | -0.458032 | 0.295402 | 0.605594 | -0.448064 | -0.466129 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Temporal Variability | 0.728280 | -0.241300 | 0.602600 | -0.567130 | -1.033755 | 0.728280 | 0.165175 | -0.074282 | -0.278690 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | ee Shape | 1.082618 | 0.661283 | 1.082618 | -0.839538 | -0.487016 | -0.264116 | -0.101133 | -0.659747 | 0.101862 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | ee Power | 1.131036 | 0.610785 | -0.404078 | 1.131036 | 0.595042 | -0.984068 | -0.557692 | -0.185367 | -0.871352 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | ee Power | 1.064486 | -0.127194 | 0.476825 | 0.464197 | 1.064486 | -0.317686 | -0.823757 | -0.801407 | -0.260839 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 2.015259 | -1.181835 | -0.182809 | 2.015259 | -0.016652 | -0.472194 | -0.872869 | -0.247147 | -0.576413 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 2.714990 | -1.026975 | 0.123590 | 2.714990 | 0.396843 | -0.519885 | -0.532213 | -0.593007 | -0.442063 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Temporal Discontinuties | 2.573240 | -1.210296 | -0.572504 | 0.789902 | 2.404007 | -1.073907 | -0.102954 | 0.351769 | 2.573240 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 2.991345 | -0.198991 | 0.131400 | 0.876118 | 2.991345 | 0.472531 | 1.398645 | 0.699440 | 1.676492 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 2.616243 | -0.377626 | -0.757495 | 0.518910 | 2.616243 | -0.754447 | -0.117472 | 0.015504 | 0.003202 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 2.283028 | -1.450637 | -0.952059 | 0.968969 | 2.283028 | 0.147307 | -0.592901 | 2.052706 | 2.208600 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 1.625207 | -0.849883 | -1.090368 | 1.625207 | -1.114524 | 0.212762 | 0.147334 | 0.669929 | 0.110630 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 1.513002 | -0.021655 | -1.232502 | 1.513002 | -1.068623 | -0.239071 | -0.318743 | 1.457929 | 0.361219 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 3.401573 | -0.604928 | -1.047398 | 3.401573 | -0.416150 | -0.489691 | 0.185927 | 0.679983 | 0.112285 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 2.634329 | -0.814963 | 0.258099 | -0.356884 | 2.634329 | -0.366966 | 1.024190 | -0.553822 | -2.057472 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 0.274191 | -0.942751 | -1.253431 | 0.274191 | -0.643670 | -0.646015 | -0.434787 | -0.234030 | -0.059013 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Temporal Variability | 1.095389 | -0.706165 | -0.749543 | 0.365136 | -0.229992 | 0.245409 | 1.095389 | -0.065466 | 0.144335 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 0.982640 | -0.932453 | 0.770863 | -1.063780 | 0.982640 | 0.657245 | -0.665694 | -0.436377 | -1.607467 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Temporal Discontinuties | 1740.517765 | 122.669262 | 227.079434 | 61.524115 | 76.991125 | 861.531663 | 843.284316 | 1432.279147 | 1740.517765 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Temporal Discontinuties | 2622.401217 | 87.175376 | 29.078072 | 197.983743 | 126.723520 | 349.336095 | 216.280259 | 2622.401217 | 1740.699192 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 1.933726 | -0.357764 | -1.083978 | 1.933726 | -0.547630 | -0.043276 | 0.317662 | 0.363933 | -0.052236 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Temporal Variability | 1.463021 | -0.104440 | -1.299248 | 0.296121 | -0.578163 | 1.463021 | -0.754036 | -1.176793 | 0.073925 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Temporal Variability | 1.976848 | -0.001426 | 0.144137 | -0.860262 | -0.167548 | 1.976848 | 0.190911 | -1.420719 | 0.094599 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 1.817392 | -0.830340 | -0.439740 | -0.765571 | 1.817392 | 1.618646 | 0.274732 | 0.844800 | 0.764062 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 2.400587 | 1.371314 | 1.323051 | 0.650999 | 2.400587 | 0.798645 | 0.106176 | -0.673897 | -1.873058 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 2.794633 | -0.860568 | 0.580531 | -0.465396 | 2.794633 | -0.364886 | 0.633537 | 0.564906 | 0.093156 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 2.561647 | 0.102340 | -0.787942 | 2.561647 | 0.404665 | -0.829704 | 0.080083 | 0.692486 | 1.176486 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 2.129037 | -0.730379 | 0.177973 | 2.129037 | 0.196745 | 0.190424 | 1.372649 | -1.394608 | 0.707049 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 3.855760 | -0.477891 | -1.091793 | 0.164828 | 3.855760 | -0.515744 | -0.910168 | -0.014909 | -0.455488 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 3.546215 | -0.584359 | 0.007480 | 3.546215 | -0.247831 | 0.704772 | 0.682953 | -0.679970 | 0.442329 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 2.117800 | -1.236827 | -0.353620 | 2.117800 | -0.399449 | -0.092951 | 0.178263 | -0.596954 | -0.367711 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 2.492016 | -0.652374 | -0.601464 | -0.060862 | 2.492016 | -1.080289 | -0.529912 | 0.431487 | -0.592200 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 3.349845 | -0.222077 | 0.665687 | 3.349845 | -0.489104 | 0.648113 | 0.133980 | -1.694407 | 0.724049 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 3.229347 | 0.568871 | 0.033941 | 0.028105 | 3.229347 | 0.473909 | 0.002923 | 0.825862 | 0.717066 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 3.487126 | -1.090945 | -0.846396 | 3.487126 | -0.051812 | 0.224948 | 0.886429 | -0.130612 | 0.004376 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 3.469513 | -0.587445 | -0.802101 | 0.142724 | 3.469513 | 2.429589 | -0.366433 | 0.672678 | 0.380612 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 2.764264 | 0.219821 | -0.207873 | -0.084478 | 2.764264 | 0.173251 | 0.970001 | -0.556844 | -0.723429 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 2.966784 | 0.774731 | -0.080685 | 2.966784 | -0.106537 | 1.627446 | 0.670219 | -0.688206 | 0.655265 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Power | 2.710010 | 0.712567 | 0.241415 | 2.710010 | -0.337809 | 1.502206 | 0.120091 | -1.018535 | 0.365129 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Shape | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 157 | N12 | digital_ok | nn Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |